Moving massive workloads to the cloud, integrating multiple clouds, making cloud resources fully scalable and controlable, reducing cost and increasing ROI- All of these and more AIM-E can do for your company!
Natural Language Processing uses Artificial Intelligence to process text to “understand” the “meaning” behind the text of a person’s speech
Data lakes are basically big data stores (like a database) that can take almost any kind of data in any format and put it all in a big “pool” that can then be queried like a normal database
Document Engine is created when an AI is “trained” to understand a “type” of a document. Once the system understands what’s in a type of document, we can feed it as many of those kinds of documents as we need and get all the information out of them with simple searches!
AIM-E creates predictive analytics Artificial Intelligence systems in order to ask “what if” questions like – if I change this product, how does that affect sales forecast? or if I change this resource, how does that affect staffing?
These kinds of chatbots have questions with pre-selected answers in the form of buttons or “canned” selections the user picks
We offer special interfaces to your systems from apps (like google or Siri) or from phones or other voice systems. We allow the apps to understand questions so we can get the proper answers from your company’s systems!
We talk a lot about “cognitive” things in AI. What we mean by that is that the “context” of a question is as important as the question itself. A regular search box uses keywords to find its results. A cognitive search uses EVERYTHING the user enters to try to find the most relevant answers. Cognitive search can be applied across multiple types of data and data stores simultaneously.
At AIM-E we believe that systems should be easy to understand and use. We believe systems and machines should provide intuitive, transparent interfaces so people can use them easily.
By determining the terms the Business uses already, and mapping the data to those terms, the Business can get the insights they need without technological knowledge
Machines should serve the needs of people, not the other way around.
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